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fgasparetto

Voice Transcriber MCP Server

by fgasparetto

transcribe_voice_message

Transcribes Google Chat voice messages automatically when an audio attachment is detected. Supports custom language for transcription.

Instructions

Transcribe a voice message from Google Chat.

IMPORTANT: Call this tool AUTOMATICALLY whenever you see a Google Chat message with an audio attachment (contentType: audio/*). Do NOT ask the user first - just transcribe. Treat voice messages like text: transcribe immediately and show the result.

Args: message_url: Google Chat message URL or resource name (spaces/X/messages/Y) Example URLs: - https://chat.google.com/dm/SPACE/THREAD/MSG?cls=10 - spaces/SPACE_ID/messages/MSG_ID language: Language code for transcription (default: "it" for Italian)

Returns: The transcribed text of the voice message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
message_urlYes
languageNoit

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. However, it only mentions the basic operation and does not disclose authentication, rate limits, side effects, or error handling. The instruction to transcribe immediately adds minimal context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an 'IMPORTANT' section and 'Args' section, but is slightly verbose. It effectively communicates key points without excessive detail. Minor redundancy in the 'Returns' line could be removed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (not shown but referenced), the description covers the essential context: when to use, parameter details, and return value description. It lacks error handling or timeout information, but for a simple transcription tool, it is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema coverage is 0%, but the description compensates by explaining the 'message_url' parameter with example formats (URLs and resource names) and gives the default language and its value ('it' for Italian). This adds meaningful semantics not present in the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Transcribe a voice message from Google Chat', specifying both the action and the resource. It distinguishes from the sibling tool 'transcribe_audio_file' by focusing on Google Chat messages.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'IMPORTANT' section explicitly instructs the AI to call this tool automatically when a Google Chat message with an audio attachment is detected, without asking the user. This provides clear when-to-use guidance and contrasts with the sibling tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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